Signals related to sensory stimuli and behavioral responses are distributed in the activity of a large number of neurons in multiple brain areas. In addition, the flow of information across different cortical areas must be controlled according to the behavioral context. Therefore, understanding the nature of communication among different groups of neurons and the physical basis for regulating such information flow would be an important step to optimize the diagnosis and treatment of various neurological conditions. The cortical network linking prefrontal cortex and posterior parietal cortex in primate brains provides a model system for investigating the nature of cortical communication, because the functional properties of individual neurons in these two cortical areas have been extensively studied. However, how the exchange of information across these two cortical areas is controlled by the behavioral task has not been systematically investigated. The proposed experiments will test the hypothesis that spike synchrony and coherent oscillation of neural activity plays an important role in context-dependent long-range cortical communication. Specifically, whether spike synchrony and coherent oscillation is related to the storage of spatial information in the working memory and whether such temporally related activity reflects the anticipation of behaviorally relevant sensory events will be tested. Also tested will be whether the frequency characteristics of such inter-areal interaction differ from those of local interaction among neurons in the same cortical area. Further experiments will determine whether the types of information stored in working memory influence the pattern of spike synchrony and coherent oscillation across the prefrontal and posterior parietal cortex. Finally, the proposed experiments will test whether temporally correlated activity underlies the integration of the animal's previous experience during decision-making process. These experiments will be performed in monkeys using two separate multi-electrode recording systems, and dynamic interaction among individual neurons will be analyzed using new analytical methods based on wavelet analysis and other standard statistical methods. The outcome of this research will advance our understanding on how the flow of behaviorally relevant information is regulated across a broad network of cortical neurons.